CSE 591 Computational Molecular Biology

Spring 2003

MW 1:40 -- 2:55 PM; PSA 113

  1. Tentative Content: 
                         * Introduction to molecular Biology
                            ( DNA, RNA, Chromososme, Genes,  Proteins, ammino acids,
                             cell dynamics, signal transduction,  Genome Organization)

                         * Introduction to active areas of research in CMB.
                            ( Human GenomeProject,  Transcription maps,  Linkage analysis,
                             Functional Genomics,  Comparative Genomics, Cell informatics,
                             Rational drug design)

                         * Introduction to algorithms.
                         * Genome Sequencing
                            (restriction enzymes, digression, restriction maps, clone library,
                             restriction maps, molecular cloning, sequence assembly,  matching rules,
                             islands and contigs, shotgun mapping, overlap rule, Genomic contig algorithm,
                             DNA ligase, hybridization, DNA amplification,  Polymerase chain reaction)

                         * Models and Algorithms
                            ( Genome sequencing algorithms: sequence reconstruction,   problem,
                              shortest superstring problem, pairwise sequence, alignment, Edit distance,
                              Scoring models,
                              multiple sequence alignment:optimal global alignment,
                              local alignment: local suffix alignment problem,
                              BLAST, FAST,  Hidden Markov modelss, Motif finding)

                         * Analysis of Gene expression data
                             (Clustering genes: microarrays, complementary  hybridization, spoted arrays,
                              Oligonucleotide arrays, cluster  analysis, hierarchical clustering, gene similarity metric,
                              Classifying Genes and gene expressions: classifying cancer,  ranking genes,
                              weighted voting, cancer class discovery, support vector,  machines,
                              Inferring regulatory networks)

                          * Phylogeny
                          * Bioinformatics Tools and Databases: data and knowledge integration
                            -- Finding paralogues by clustering (BLASTCLUST, CD-HIT)
                             -- Finding homologues and Orthologues (BLAST)
                             -- Finding remote homologues (PSI-BLAST)
                             -- Finding functional annotation (PFAM, INTERPRO)
                             -- Finding structural annotation (Blast PDB)
                             -- Finding low complex regions (SEG, CAST)
                             -- Finding transmembrane regions (TMHMM)
                             -- Finding disordered regions (COILS, PONDR)
                             -- Finding secondary structure (JPRED, TOPpred)
                             -- NCBI, EBI, PDB, PFAM

  1.     Textbook and CD-ROM:
                Bioinformatics: Sequence and Genome Analysis -- David Mount
                Roche Genetics Education program CD from www.rochegenetics.com

     3.      Referenec Books:

                Biological Sequence analysis: probabilistic models of proteins and nucleic acids --
                                Durbin, Eddy, Krogh and Mitchison
                Computational molecular biology: an algorithmic approach   -- Pevzner
                Computational methods in molecular biology  -- edited by Salzberg, Searls and Kasif.
                 Discovering Genomics, Proteomics and Bioinformatics --
                               A. Malcolm Campbell and Laurie J. Heyer.
                 A Practical Approach to Microarray Data Analysis.  -- edited by Daniel P. Berrar,
                                Werner Dubitzky, and Martin Granzow, Kluwer.

     4.     Grading (tentative and subject to change): 

                        40 % Two Class tests (Mid March and Last day of Class)  (No finals)
                        40 % Project  
                        20 % Homework, Presentation, Notetaking